Abstract: With petascale computing power on the immediate horizon, computational studies have the opportunity to make unprecedented contributions to drug discovery efforts. Although ligand flexibility is routinely accounted for in computer-aided drug design (CADD) methodologies, incorporating receptor flexibility and system complexity remains an important challenge. The next frontier in flexible receptor methodologies is the integration of cutting-edge physics-based computational methods into the CADD techniques, in conjunction with the use of more complex biological systems. The incorporation of powerful new predictive theoretical tools into flexible receptor methodologies for ligand discovery and design will provide an important shift to the CADD field, enabling the discovery of novel ligand-binding modes and expediting the estimation of more accurate ligand free energies of binding. My vision is to drive the computer-aided drug design field towards a systems biology approach, where multiple proteins, and the RNAs they bind, are targeted - thus challenging the "one-target, one- disease, one-drug" paradigm. The new approaches I envision will integrate multiple time and length scales and take explicit advantage of the new structural information yielded by these algorithms. These investigations will push important frontiers in our understanding of biology, ultimately opening new pathways to more effective therapeutics. Public Health Relevance: With petascale computing power on the immediate horizon, computational studies have the opportunity to make unprecedented contributions to drug discovery efforts. The next frontier in flexible receptor methodologies is the integration and streamlining of cuttingedge physics-based computational methods into computer-aided drug design. The results of this work will catalyze the broader use of these methods within the biomedical research community and be applicable to a wide range of drug targets that are extremely relevant to global health.